The approaches described in this section could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section. Furthermore, all embodiments are not necessarily intended to solve all or even any of the problems brought forward in this section.
The Third Generation Partnership Project (3GPP) Long-Term Evolution (LTE) standardization efforts have chosen the Multiple Input Multiple Output (MIMO) antennas system for the downlink (DL) radio transmission due to its nature of spatial division multiplexing, which brings a significant spectral efficiency improvement.
There is a wide agreement that multi-user MIMO (MU-MIMO) allows for better exploitation of multi-user diversity. The MU-MIMO system has multiple users served at the same time on the same subcarrier by means of spatial separation. The main challenge in MU-MIMO is that not all receive antennas can cooperate and, therefore, the transmitter has to take care of the inter-user interference by several means that includes the design of the precoders for spatial user separation as well as the scheduling for exploitation of multi-user diversity. It has been found that the throughput gain of MU-MIMO system highly depends on exploiting the multi-user diversity available in the system.
The MIMO system can be built in distributed antenna system (DAS) where many remote antenna ports are distributed over a large area and connected to a central processor by fiber, coax cable, or microwave link. In 3GPP's discussion, DAS is referred as Coordinated Multi-Point transmission/reception (CoMP) system. To be more specific, DAS in 3GPP-LTE is a system comprising a base station (BS) equipped with an extremely powerful base band unit (BBU), and several remote radio units (RRUs) connected to BBU, for example over high-speed optical fibers. These systems are used to cover a large geographical area (e.g. hundreds of meters). The base band processing as well as radio resource and network management functionalities are included in the BBU, while RRU usually equipped with multiple antennas is responsible for the conversion between radio frequency (RF) and digital intermediate frequency (IF) signals. Multiple user equipments (UEs) can get paired to collaborate with each other for transmission.
Currently, several versions of linear precoding have been discussed for standardization in 3GPP-LTE system in frequency division duplex (FDD) mode. There are basically two kinds of precoding schemes taken into consideration: channel vector quantization (CVQ) and per user unitary and rate control (PU2RC).
In CVQ, feedback from UE indicates a codebook entry, where the codebook contains quantized versions of a channel vector estimated by the UE. At the BS, the zero-forcing precoders are calculated with the UEs' feedback.
PU2RC defines the codebook that contains not quantized versions of the channel vectors themselves but possible precoding vectors. Then, the feedback received by the BS actually indicates a preferred precoder from a set of predefined precoders. In other words, the calculation of precoders is not needed at the BS.
Since the scheduling schemes should operate in conjunction with the precoding schemes, two scheduling schemes corresponding to the precoding schemes mentioned above are presented to select the UEs for DL transmission. One is corresponding to PU2RC precoding scheme. It is to group UEs that report orthogonal precoding vectors and select the group providing the highest total throughput. Another more general and greedy strategy is appropriate for CVQ precoding schemes, consists of adding one UE at a time, as long as the additional UE increases the overall throughput. It has been released that CVQ scheme generally is preferable over PU2RC scheme. Hence, CVQ is the mainstream strategy of DL transmission in 3GPP-LTE FDD MU-MIMO system.
In CVQ discussed in 3GPP-LTE, each UE selects a quantization vector ĥk, from a codebook of unit-norm row vectors of size N=2B (B being an integer), which is expressed as:C={c1, . . . ,cN}  (1)
Quantization vector ĥk is determined according to the minimum Euclidean distance criterion, such that:
                                                        h              ^                        k                    =                      c            n                          ,                              arg            ⁢                                                  ⁢                                          max                                                      i                    =                    1                                    ,                  …                  ⁢                                                                          ,                  N                                            ⁢                                                                                    h                    k                                    ⁢                                                            h                      ^                                        i                    H                                                                                                =                      arg            ⁢                                                  ⁢                                          max                                                      i                    =                    1                                    ,                  …                  ⁢                                                                          ,                  N                                            ⁢                                                                                          n                      ·                                              M                        c                                                                                    T                      k                                                                      ⁢                                                                                              h                      k                                        ⁢                                                                  h                        ^                                            i                      H                                                                                                                                                (        2        )            
The codebook C is previously known to all the UEs and the BS. It is usually defined as the Discrete Fourier Transformation (DFT) matrix where the quantization vectors are obtained by truncating the top rows of the DFT matrix of size N. Each UE estimates its actual channel and feeds back the index n to the BS with B bits. Normally, n is considered as the channel direction information (CDI) of k-th UE.
In addition to CDI, namely the codebook index n, the BS should have the UE report the estimated channel quality information (CQI) expressed as:
                              CQI          k                =                                                                                                                                 ⁢                P                                            M                t                                      ⁢                                                                                                h                    k                                    ⁢                                                            h                      ^                                        k                    H                                                                              2                                            1            +                                                                                                                                         ⁢                  P                                                  M                  t                                            ⁢                              (                                                                                                                          h                        k                                                                                    2                                    -                                                                                                                                    h                          k                                                ⁢                                                                              h                            ^                                                    k                          H                                                                                                            2                                                  )                                                                        (        3        )            
where Mt is the number of transmit antenna, =P/N0 and N0 is the noise power. It is observed that the channel information used for the user scheduling in MU-MIMO system includes two components: CDI and CQI.
At the BS, the assembled precoding matrix is given by:G(S)=Ĥ(S)H(Ĥ(S)Ĥ(S)H)−1diag(p)1/2  (4)
where S={s1, . . . , s|S|} is the set of UEs selected for transmission. Ĥ(S)=[ĥs1T, . . . , ĥs|S|T]T represents the concatenated quantized channel vectors of the selected users and p=(ps1, . . . , ps|S|)T is the vector of power normalization coefficients that impose the power constraint on the transmitted signal. As the total power P is assumed to be allocated equally to each transmit antenna, we have:
                              p          k                =                              P                                        S                                              ⁢                      1                                                                            f                  k                                                            2                                                          (        5        )            
where fk denotes the k-th column of F(S)=Ĥ(S)H(Ĥ(S)Ĥ(S)H)−1.
Denote with R(S) the achievable sum-rate when the set of users S is selected for transmission and the amount of transmit antennas is Mt. Then, the scheduling method for user selection can be described as following:
TABLE 1 Initialise S = ∅  and R(S) = 0While |S| ≦Mt             1      )        ⁢                  ⁢    find    ⁢                  ⁢          k      *        =      arg    ⁢                  ⁢                  max                  k          ≠          S                    ⁢              R        ⁡                  (                      S            ⋃                          {              k              }                                )                      2) if R(S ∪ {k*}) > R(S) update S = S ∪ {k*}
In scheduling stage, R(S) can be computed as:
                              R          ⁡                      (            S            )                          =                              ∑                          k              ∈              S                                ⁢                                          ⁢                                    log              2                        ⁡                          (                              1                +                                  γ                  k                                            )                                                          (        6        )            
where γk is the SINR of user k and given by:
                              γ          k                =                                            p              k                                      P              /                              M                t                                              ⁢                      CQI            k                                              (        7        )            
In addition to the above methods currently presented by 3GPP LTE-A, another proposal has been proposed in patent application WO 2011/077260 to improve the system throughput in the MU-MIMO built based on DAS. The proposed strategy is similar to the traditional LTE-A defined CVQ schemes except two points: (1) BS constructs the UE specific channel vector for scheduling, and (2) UE takes new method to compute its CQI.
To create the UE specific channel vector, the UE may send out reference signals called as sounding reference signal (SRS) to the BS for uplink measurement. Then BS may estimate whether its signal can reach UE via checking the SRS from UE. We define a channel invisibility vector as:
                              V                      k            ,            j                          =                  {                                                    1                                                                                  S                                          k                      ,                      j                                                        ≥                  α                                                                                    0                                                                                  S                                          k                      ,                      j                                                        <                  α                                                                                        (        9        )            
where Si,j denotes the strength of SRS from UE i to RRU j, and α is the receiver sensitivity of the UEs. Although there is no channel reciprocity between uplink and downlink in FDD system, it is practical to use SRS over uplink to estimate the possibility that signal over downlink can reach the UE because the link budget estimation prior to the system deployment can ensure the downlink signal is visible to UE as long as the BS is able to detect the signal from UE.
After having channel feedback ĥk and Vk, the BS can construct the channel vector oriented to UE k as:
                                          h            ~                    k                =                                            h              ^                        k                    ·                      diag            ⁡                          (                                                V                  k                                ·                                                                            n                      ·                                              M                        e                                                                                    T                      k                                                                                  )                                                          (        10        )            
where n is the number of RRUs, Me is the amount of antennas in each RRU, and Tk refers to the number of the transmit antennas whose signal can be received by the UE. Generally, we have:Tk=sum(Vk)  (11)Tk≦Mt  (12)
where sum(•) represents the sum of the elements of the vector, and √{square root over (n·Me/Tk)} ensures that the norm of {tilde over (h)}k is 1.
In the scheduling stage, the BS exploits the channel vector {tilde over (h)}k instead of the quantization vector ĥk to calculate the precoding matrix and the user set for transmission.
On the other hand, at the side of UE, the CQI for feedback is calculated as:
                              CQI          k          new                =                                                                                                                                 ⁢                P                                            T                k                                      ⁢                                                                                                h                    k                                    ⁢                                                            h                      ^                                        k                    H                                                                              2                                            1            +                                                                                                                                         ⁢                  P                                                  n                  ·                                      M                    e                                                              ⁢                              (                                                                                                                          h                        k                                                                                    2                                    -                                                                                    n                        ·                                                  M                          e                                                                                            T                        k                                                              ⁢                                                                                                                                                h                            k                                                    ⁢                                                                                    h                              ^                                                        k                            H                                                                                                                      2                                                                      )                                                                        (        13        )            
Although DAS in 3GPP-LTE is helpful to increase system capacity and coverage, the current precoding schemes and scheduling methods, especially the CVQ method, may select excessive users with significant inter-user interference when they are used in distributed antenna architecture architectures.
Since the RRUs are dispersedly located around UE and may have totally different propagation path to the UE, it is possible that UE detects the signal strength of these RRUs as 0, meaning that the received signal has strength below the sensitivity of the UE's receiver due to the deep attenuation.
Thus, the actual channel vector estimated by the UE should have several elements of 0, and then the assembled channel matrix H(s) experienced by the transmitted signal is:H(S)={{tilde over (H)}K×LOK×Q},L+Q=Mt  (14)
where {tilde over (H)}K×L is the channel gain elements larger than 0, OK×Q is the elements whose values are 0, K is the number of selected users, and the number of RRUs is L+Q=Mt.
It has to be noted that L+Q should be no less than number K to ensure the null-interference transmission. However, the BS assumes wrongly that the signal from all the transmit antennas can be received by the UEs because the quantization vectors reported by the UEs have not the elements of 0. Then it is possible that the BS may select more than L+Q users and generate the wrong precoding matrix, which inevitably leads to significant inter-user interference.
On the other hand, from the perspective of channel quantization, there is always significant quantization error in UEs' feedback since the signal from some of the RRUs cannot be detected by UEs. Thus, the quantization error between the actual channel vectors and the feedback vectors may always exist as well. Since the quantization error degrades the system throughput greatly, it is obvious that the traditional CVQ method is not sufficient to achieve the high throughput in an architecture with distributed antennas.
The method presented in WO 2011/077260 achieves performance improvement by relying on the DL signal separation due to the space barrier. In other words, the radio signal from the BS's antennas can be attenuated by the spatial elements such as distance and physical barrier.
However, when there is no strong spatial signal separation over downlink, the BS cannot achieve performance improvement as compared with the method presented in 3GPP LTE-A.
The invention will improve the situation.